# xarray.Dataset.query

#### Dataset.query(queries=None, parser='pandas', engine=None, missing_dims='raise', \*\*queries_kwargs)[[source]](https://github.com/pydata/xarray/blob/main/xarray/core/dataset.py#L9934-L10028)

Return a new dataset with each array indexed along the specified
dimension(s), where the indexers are given as strings containing
Python expressions to be evaluated against the data variables in the
dataset.

* **Parameters:**
  * **queries** ([dict-like](https://docs.python.org/3/glossary.html#term-mapping), *optional*) – A dict-like with keys matching dimensions and values given by strings
    containing Python expressions to be evaluated against the data variables
    in the dataset. The expressions will be evaluated using the pandas
    eval() function, and can contain any valid Python expressions but cannot
    contain any Python statements.
  * **parser** (`{"pandas", "python"}`, *default*: `"pandas"`) – The parser to use to construct the syntax tree from the expression.
    The default of ‘pandas’ parses code slightly different than standard
    Python. Alternatively, you can parse an expression using the ‘python’
    parser to retain strict Python semantics.
  * **engine** (`{"python", "numexpr", None}`, *default*: [`None`](https://docs.python.org/3/builtins/constants.html#None)) – The engine used to evaluate the expression. Supported engines are:
    - None: tries to use numexpr, falls back to python
    - “numexpr”: evaluates expressions using numexpr
    - “python”: performs operations as if you had eval’d in top level python
  * **missing_dims** (`{"raise", "warn", "ignore"}`, *default*: `"raise"`) – What to do if dimensions that should be selected from are not present in the
    Dataset:
    - “raise”: raise an exception
    - “warn”: raise a warning, and ignore the missing dimensions
    - “ignore”: ignore the missing dimensions
  * **\*\*queries_kwargs** (`{dim: query, ...}`, *optional*) – The keyword arguments form of `queries`.
    One of queries or queries_kwargs must be provided.
* **Returns:**
  **obj** ([`Dataset`](xarray.Dataset.html.md#xarray.Dataset)) – A new Dataset with the same contents as this dataset, except each
  array and dimension is indexed by the results of the appropriate
  queries.

#### SEE ALSO
[`Dataset.isel`](xarray.Dataset.isel.html.md#xarray.Dataset.isel), [`pandas.eval`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.eval.html#pandas.eval)

### Examples

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```pycon
>>> a = np.arange(0, 5, 1)
>>> b = np.linspace(0, 1, 5)
>>> ds = xr.Dataset({"a": ("x", a), "b": ("x", b)})
>>> ds
<xarray.Dataset> Size: 80B
Dimensions:  (x: 5)
Dimensions without coordinates: x
Data variables:
    a        (x) int64 40B 0 1 2 3 4
    b        (x) float64 40B 0.0 0.25 0.5 0.75 1.0
>>> ds.query(x="a > 2")
<xarray.Dataset> Size: 32B
Dimensions:  (x: 2)
Dimensions without coordinates: x
Data variables:
    a        (x) int64 16B 3 4
    b        (x) float64 16B 0.75 1.0
```

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